Breaking Fault Lines: Unifying TEE-Assisted BFT Consensus in Partially Trusted Worlds

2026-09-09

AI Summary

本文研究了部分可信环境下的TEE辅助BFT共识问题，通过引入双重仲裁构造和TEE领导者快速路径方法，提高了系统的容错性和性能。

Abstract

This paper revisits TEE-assisted BFT under a universal partial-TEE model, where an arbitrary subset of replicas execute inside TEEs while the remaining replicas operate without hardware trust guarantees. We show that heterogeneous trust changes the structure of quorum formation and fault tolerance. In particular, we derive a tight resilience bound f < max {n/3, m/2}, where n is the total number of replicas and m is the number of TEE-enabled replicas. The result reveals a sharp threshold phenomenon: TEEs improve fault tolerance only once they exceed two-thirds of the deployment. Guided by this characterization, we introduce two protocol principles: (1) a dual-quorum construction that safely combines TEE-only and mixed quorums, and (2) a TEE-leader fast path that leverages hardware-enforced non-equivocation to reduce both consensus and view-change latency. We realize these ideas in Raftel, which is, to our knowledge, the first HotStuff-style BFT protocol designed explicitly for arbitrary partial-TEE deployments, and in chained-Raftel, a pipelined variant that further accelerates mixed-trust execution. We implement both protocols atop Intel SGX and evaluate them in LAN and WAN environments. Our results show that Raftel achieves up to 625 TPS with sub-670 ms latency in WAN settings, outperforming HotStuff by up to 308 TPS in throughput while approaching the performance of fully TEE-assisted protocols.

Problem

• TEE-assisted BFT
• partial-TEE model
• fault tolerance
• quorum formation
• heterogeneous trust

Innovation

• partial-TEE model
• dual-quorum construction
• TEE-leader fast path
• Raftel